Extra-Nuclear Signalling of Estrogen Receptor to Breast Cancer Cytoskeletal Remodelling, Migration and Invasion

BACKGROUND: Estrogen is an established enhancer of breast cancer development, but less is known on its effect on local progression or metastasis. We studied the effect of estrogen receptor recruitment on actin cytoskeleton remodeling and breast cancer cell movement and invasion. Moreover, we characterized the signaling steps through which these actions are enacted. METHODOLOGY/PRINCIPAL FINDINGS: In estrogen receptor (ER) positive T47-D breast cancer cells ER activation with 17beta-estradiol induces rapid and dynamic actin cytoskeleton remodeling with the formation of specialized cell membrane structures like ruffles and pseudopodia. These effects depend on the rapid recruitment of the actin-binding protein moesin. Moesin activation by estradiol depends on the interaction of ER alpha with the G protein G alpha(13), which results in the recruitment of the small GTPase RhoA and in the subsequent activation of its downstream effector Rho-associated kinase-2 (ROCK-2). ROCK-2 is responsible for moesin phosphorylation. The G alpha(13)/RhoA/ROCK/moesin cascade is necessary for the cytoskeletal remodeling and for the enhancement of breast cancer cell horizontal migration and invasion of three-dimensional matrices induced by estrogen. In addition, human samples of normal breast tissue, fibroadenomas and invasive ductal carcinomas show that the expression of wild-type moesin as well as of its active form is deranged in cancers, with increased protein amounts and a loss of association with the cell membrane. CONCLUSIONS/SIGNIFICANCE: These results provide an original mechanism through which estrogen can facilitate breast cancer local and distant progression, identifying the extra-nuclear G alpha(13)/RhoA/ROCK/moesin signaling cascade as a target of ER alpha in breast cancer cells. This information helps to understand the effects of estrogen on breast cancer metastasis and may provide new targets for therapeutic interventions

Arteriopathy diagnosis in childhood arterial ischemic stroke: results of the vascular effects of infection in pediatric stroke study.

Background and purposeAlthough arteriopathies are the most common cause of childhood arterial ischemic stroke, and the strongest predictor of recurrent stroke, they are difficult to diagnose. We studied the role of clinical data and follow-up imaging in diagnosing cerebral and cervical arteriopathy in children with arterial ischemic stroke.MethodsVascular effects of infection in pediatric stroke, an international prospective study, enrolled 355 cases of arterial ischemic stroke (age, 29 days to 18 years) at 39 centers. A neuroradiologist and stroke neurologist independently reviewed vascular imaging of the brain (mandatory for inclusion) and neck to establish a diagnosis of arteriopathy (definite, possible, or absent) in 3 steps: (1) baseline imaging alone; (2) plus clinical data; (3) plus follow-up imaging. A 4-person committee, including a second neuroradiologist and stroke neurologist, adjudicated disagreements. Using the final diagnosis as the gold standard, we calculated the sensitivity and specificity of each step.ResultsCases were aged median 7.6 years (interquartile range, 2.8-14 years); 56% boys. The majority (52%) was previously healthy; 41% had follow-up vascular imaging. Only 56 (16%) required adjudication. The gold standard diagnosis was definite arteriopathy in 127 (36%), possible in 34 (9.6%), and absent in 194 (55%). Sensitivity was 79% at step 1, 90% at step 2, and 94% at step 3; specificity was high throughout (99%, 100%, and 100%), as was agreement between reviewers (κ=0.77, 0.81, and 0.78).ConclusionsClinical data and follow-up imaging help, yet uncertainty in the diagnosis of childhood arteriopathy remains. This presents a challenge to better understanding the mechanisms underlying these arteriopathies and designing strategies for prevention of childhood arterial ischemic stroke

O impacto, sobre estudantes brasileiros, de uma linguagem visual para aprender a aprender conjuntamente

Resumo Um dos temas mais importantes na aprendizagem colaborativa apoiada pelo computador é a autorregulação da aprendizagem sem o apoio de professores. A autorregulação da colaboração pode ser definida como o conjunto dos processos sociais que os alunos usam para coordenar o seu esforço conjunto em uma atividade. Este trabalho apresenta um estudo de caso brasileiro que examina o impacto da plataforma computacional Metafora para apoiar a regulação da colaboração entre os estudantes brasileiros. Nosso objetivo é investigar se o uso da linguagem visual Metafora ajuda os alunos a aprenderem a aprender em conjunto (learn to learn togueter – L2L2). L2L2 abrange o desenvolvimento da capacidade de coordenação da colaboração. Para perseguir esse objetivo, são fornecidas evidências de mecanismos de coordenação e as respostas emocionais subjacentes ao uso, pelos alunos, da ferramenta de planejamento Metafora. Os resultados deste estudo de caso demonstram que as interações dos alunos, ao usarem a ferramenta de planejamento Metafora, influenciaram o seu desenvolvimento de L2L2 de maneira natural e envolvente. A ferramenta de planejamento Metafora proporciona aos alunos um ambiente amigável para a regulação dos processos de grupo e tem potencial para modificar os pensamentos dos estudantes com respeito à coordenação de processos colaborativos

Risk of Recurrent Arterial Ischemic Stroke in Childhood: A Prospective International Study.

Background and purposePublished cohorts of children with arterial ischemic stroke (AIS) in the 1990s to early 2000s reported 5-year cumulative recurrence rates approaching 20%. Since then, utilization of antithrombotic agents for secondary stroke prevention in children has increased. We sought to determine rates and predictors of recurrent stroke in the current era.MethodsThe Vascular Effects of Infection in Pediatric Stroke (VIPS) study enrolled 355 children with AIS at 37 international centers from 2009 to 2014 and followed them prospectively for recurrent stroke. Index and recurrent strokes underwent central review and confirmation, as well as central classification of causes of stroke, including arteriopathies. Other predictors were measured via parental interview or chart review.ResultsOf the 355 children, 354 survived their acute index stroke, and 308 (87%) were treated with an antithrombotic medication. During a median follow-up of 2.0 years (interquartile range, 1.0-3.0), 40 children had a recurrent AIS, and none had a hemorrhagic stroke. The cumulative stroke recurrence rate was 6.8% (95% confidence interval, 4.6%-10%) at 1 month and 12% (8.5%-15%) at 1 year. The sole predictor of recurrence was the presence of an arteriopathy, which increased the risk of recurrence 5-fold when compared with an idiopathic AIS (hazard ratio, 5.0; 95% confidence interval, 1.8-14). The 1-year recurrence rate was 32% (95% confidence interval, 18%-51%) for moyamoya, 25% (12%-48%) for transient cerebral arteriopathy, and 19% (8.5%-40%) for arterial dissection.ConclusionsChildren with AIS, particularly those with arteriopathy, remain at high risk for recurrent AIS despite increased utilization of antithrombotic agents. Therapies directed at the arteriopathies themselves are needed

Reversible optical switching memristors with tunable STDP synaptic plasticity: a route to hierarchical control in artificial intelligent systems

Optical control of memristors opens the route to new applications in optoelectronic switching and neuromorphic computing. Motivated by the need for reversible and latched optical switching we report on the development of a memristor with electronic properties tunable and switchable by wavelength and polarization specific light. The device consists of an optically active azobenzene polymer, poly(disperse red 1 acrylate), overlaying a forest of vertically aligned ZnO nanorods. Illumination induces trans- cis isomerization of the azobenzene molecules, which expands or contracts the polymer layer and alters the resistance of the off/on states, their ratio and retention time. The reversible optical effect enables dynamic control of a memristors learning properties including control of synaptic potentiation and depression, optical switching between short -term and long-term memory and optical modulation of the synaptic efficacy via spike timing dependent plasticity. The work opens the route to the dynamic patterning of memristor networks both spatially and temporally by light, thus allowing the development of new optically reconfigurable neural networks and adaptive electronic circuits

Location analysis for the estrogen receptor-α reveals binding to diverse ERE sequences and widespread binding within repetitive DNA elements

Location analysis for estrogen receptor-α (ERα)-bound cis-regulatory elements was determined in MCF7 cells using chromatin immunoprecipitation (ChIP)-on-chip. Here, we present the estrogen response element (ERE) sequences that were identified at ERα-bound loci and quantify the incidence of ERE sequences under two stringencies of detection: <10% and 10–20% nucleotide deviation from the canonical ERE sequence. We demonstrate that ∼50% of all ERα-bound loci do not have a discernable ERE and show that most ERα-bound EREs are not perfect consensus EREs. Approximately one-third of all ERα-bound ERE sequences reside within repetitive DNA sequences, most commonly of the AluS family. In addition, the 3-bp spacer between the inverted ERE half-sites, rather than being random nucleotides, is C(A/T)G-enriched at bona fide receptor targets. Diverse ERα-bound loci were validated using electrophoretic mobility shift assay and ChIP-polymerase chain reaction (PCR). The functional significance of receptor-bound loci was demonstrated using luciferase reporter assays which proved that repetitive element ERE sequences contribute to enhancer function. ChIP-PCR demonstrated estrogen-dependent recruitment of the coactivator SRC3 to these loci in vivo. Our data demonstrate that ERα binds to widely variant EREs with less sequence specificity than had previously been suspected and that binding at repetitive and nonrepetitive genomic targets is favored by specific trinucleotide spacers

Neurologic Involvement in Children and Adolescents Hospitalized in the United States for COVID-19 or Multisystem Inflammatory Syndrome

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Importance Coronavirus disease 2019 (COVID-19) affects the nervous system in adult patients. The spectrum of neurologic involvement in children and adolescents is unclear. Objective To understand the range and severity of neurologic involvement among children and adolescents associated with COVID-19. Setting, Design, and Participants Case series of patients (age <21 years) hospitalized between March 15, 2020, and December 15, 2020, with positive severe acute respiratory syndrome coronavirus 2 test result (reverse transcriptase-polymerase chain reaction and/or antibody) at 61 US hospitals in the Overcoming COVID-19 public health registry, including 616 (36%) meeting criteria for multisystem inflammatory syndrome in children. Patients with neurologic involvement had acute neurologic signs, symptoms, or diseases on presentation or during hospitalization. Life-threatening involvement was adjudicated by experts based on clinical and/or neuroradiologic features. Exposures Severe acute respiratory syndrome coronavirus 2. Main Outcomes and Measures Type and severity of neurologic involvement, laboratory and imaging data, and outcomes (death or survival with new neurologic deficits) at hospital discharge. Results Of 1695 patients (909 [54%] male; median [interquartile range] age, 9.1 [2.4-15.3] years), 365 (22%) from 52 sites had documented neurologic involvement. Patients with neurologic involvement were more likely to have underlying neurologic disorders (81 of 365 [22%]) compared with those without (113 of 1330 [8%]), but a similar number were previously healthy (195 [53%] vs 723 [54%]) and met criteria for multisystem inflammatory syndrome in children (126 [35%] vs 490 [37%]). Among those with neurologic involvement, 322 (88%) had transient symptoms and survived, and 43 (12%) developed life-threatening conditions clinically adjudicated to be associated with COVID-19, including severe encephalopathy (n = 15; 5 with splenial lesions), stroke (n = 12), central nervous system infection/demyelination (n = 8), Guillain-Barré syndrome/variants (n = 4), and acute fulminant cerebral edema (n = 4). Compared with those without life-threatening conditions (n = 322), those with life-threatening neurologic conditions had higher neutrophil-to-lymphocyte ratios (median, 12.2 vs 4.4) and higher reported frequency of D-dimer greater than 3 μg/mL fibrinogen equivalent units (21 [49%] vs 72 [22%]). Of 43 patients who developed COVID-19–related life-threatening neurologic involvement, 17 survivors (40%) had new neurologic deficits at hospital discharge, and 11 patients (26%) died. Conclusions and Relevance In this study, many children and adolescents hospitalized for COVID-19 or multisystem inflammatory syndrome in children had neurologic involvement, mostly transient symptoms. A range of life-threatening and fatal neurologic conditions associated with COVID-19 infrequently occurred. Effects on long-term neurodevelopmental outcomes are unknown

EURASIP Journal on Applied Signal Processing 2005:13, 2043–2053 c ○ 2005 Hindawi Publishing Corporation Coarse Fingerprint Registration Using Orientation Fields

The majority of traditional research into automated fingerprint identification has focused on algorithms using minutiae-based features. However, shortcomings of this approach are becoming apparent due to the difficulty of extracting minutiae points from noisy or low-quality images. Therefore, there has been increasing interest in algorithms based on nonminutiae features in recent years. One vital stage in most fingerprint verification systems is registration, which involves recovering the transformation parameters that align features from each fingerprint. This paper investigates the use of orientation fields for registration; an approach that has the potential to perform robustly for poor-quality images. Three diverse algorithms have been implemented for the task. The first algorithm is based on the generalized Hough transform, and it works by accumulating evidence for transformations in a discretized parameter space. The second algorithm is based on identifying distinctive local orientations, and using these as landmarks for alignment. The final algorithm follows the path of steepest descent in the parameter space to quickly find solutions that are locally optimal. The performance of these three algorithms is evaluated using an FVC2002 dataset

Hierarchical fingerprint verification

Fingerprints have been an invaluable tool for law enforcement and forensics for over a century, motivating research into automated fingerprint based identification in the early 1960's. More recently, fingerprints have found an application in the emerging industry of biometric systems. Biometrics is the automatic identification of an individual based on physiological or behavioral characteristics. Due to its security related applications and the current world political climate, biometrics is presently the subject of intense research by private and academic institutions. Fingerprints are emerging as the most common and trusted biometric for personal identification. However, despite decades of intense research there are still significant challenges for the developers of automated fingerprint verification systems. This thesis includes an examination of all major stages of the fingerprint verification process, with contributions made at each step. The primary focus is upon fingerprint registration, which is the challenging problem of aligning two prints in order to compare their corresponding features for verification.A hierarchical approach is proposed consisting of three stages,each of which employs novel features and techniques for alignment.Experimental results show that the hierarchical approach is robust and outperforms competing state-of-the-art registration methods from the literature. However, despite its power, like most algorithms it has limitations. Therefore, a novel method of information fusion at the registration level has been developed. The technique dynamically selects registration parameters from a set of competing algorithms using a statistical framework. This allows for the relative advantages of different approaches to be exploited.The results show a significant improvement in alignment accuracy for a wide variety of fingerprint databases. Given a robust alignment of two fingerprints, it still remains to be verified whether or not they have originated from the same finger. This is a non-trivial problem, and a close examination of fingerprintfeatures available for this task is conducted with extensive experimental results